Federal Housing Finance Agency Print
Home / Supervision & Regulation / Federal Register / Supervision & Regulation

Date:
03/21/2019
Name:
Gerron Levi
City:
Washington
State:
District of Columbia
Organization:
National Community Reinvestment Coalition
Rule Number:
Federal Register Citation:
83 FR 65575
CFR:
12 CFR Part 1254

Comment

March 21, 2019


Alfred M. Pollard 
General Counsel
Federal Housing Finance Agency, Eighth Floor
400 7th Street, SW
Washington, D.C. 20219

Attention: Comments/RIN 2590–AA98)

Dear Mr. Pollard:  

We appreciate the opportunity to comment on the Federal Housing Finance Agency’s (FHFA) notice of proposed rulemaking on credit score models.  For more than 25 years, the National Community Reinvestment Coalition (NCRC) and our members have been focused on creating opportunities for people and communities to build and maintain wealth, and accessing homeownership is key.  NCRC members include community reinvestment organizations, community development corporations, local and state government agencies, faith-based institutions, fair housing and civil rights groups, minority and women-owned business associations, housing counselors, and social service providers from across the nation.
New credit scoring models and responsible alternative data sources can benefit borrowers and investors
Credit scores measure the relative likelihood of a borrower making their payments on time. While credit scores are just one of many attributes used in the automated underwriting processes at Fannie Mae and Freddie Mac (the Enterprises), credit scores drive important decisions at the Enterprises that can determine access and affordability for low- and moderate-income (LMI) and minority borrowers, including mortgage product eligibility and loan pricing.  The Enterprises have been using Classic FICO for more than 12 years.  During that time, the credit scoring and consumer credit data landscape has evolved in significant ways.  
Newer credit scoring models lessen the impact of medical debts and exclude third-party collections that have been paid, contain better information on student loan performance and some rental payments data.  In addition, other data providers are pioneering alternative sources of data, outside that maintained by the three national credit reporting agencies (CRAs), such as more comprehensive rental payments information.   FICO XD score, for example, uses alternative data sources from specialty consumer reporting agencies such as the National Consumer Telcom and Utilities Exchange (NCTUE) for individuals who have either no credit history or too little credit history to generate a traditional FICO score.  VantageScore has demonstrated that it can score approximately 40 million people who are unable to obtain a score using the Classic FICO scoring model, and the company estimates that approximately 10 million of those would have a score of 620 or above possibly making them mortgage eligible under Enterprise guidelines.  A significant share is estimated to be African-American or Hispanic, segments that have had difficulty accessing affordable mortgage credit and homeownership.
FHFA’s Request for Information last year acknowledged that newer credit scoring models improve accuracy in ways that would ultimately benefit borrowers and investors and that they have incorporated economic changes since the financial crisis.   We believe millions of LMI and minority borrowers could potentially access more suitable mortgage products and/or better loan pricing with newer and more accurate credit scoring models and with responsible innovations in credit data sources.  As in other areas of the mortgage market, the Enterprises could do more within a test-and-learn or pilot framework to facilitate greater access to mortgage credit for LMI and minority borrowers that have thin credit files that do not allow for a traditional credit score.  Both Enterprises, for example, have recently updated their automated underwriting systems to evaluate mortgage applications when the borrower does not have a credit score.    We support FHFA allowing a pilot for “supplemental” credit scores for those borrowers that rely on alternative data sources, as well as pilots that test data from alternative providers that might responsibly expand mortgage eligibility and/or improve pricing for traditionally underserved borrowers that lack a credit score.  
Mitigate the cost of validation, adoption and transition for low-and moderate-income borrowers
The agency has also indicated that updating the Enterprises’ credit score requirements will result in the entire mortgage finance industry incurring operations and transition costs that could result in higher borrowing costs for consumers.  We urge FHFA to take steps to mitigate any cost impact for LMI borrowers.  Many LMI borrowers are already facing significant increases in borrowing cost post-crisis, including a 250% increase in the Enterprises’ guarantee fees since 2009, Loan Level Price Adjustments (LLPAs) at Fannie Mae and Post Settlement Delivery Fees at Freddie Mac.   In that regard, the costs associated with validating and approving an applicant’s credit score model as well as data acquisition should be reasonable and not impose undue costs on credit score developers and data providers innovating in the marketplace to expand responsible access to credit and should not be borne by LMI borrowers.  Improvements in accuracy benefit the mortgage finance system more broadly and should not disproportionately fall on LMI consumers.
 FHFA and the Enterprises can take steps to lessen any anticompetitive effects 
FHFA’s proposal raises a number of complicated considerations around competition and industry consolidation.  FHFA has acknowledged and we agree that newer credit scores improve accuracy and could benefit borrowers and investors.  We do not believe that the common ownership structure of some credit score developers and data providers alone should preclude an applicant’s ability to compete since other steps can be taken to lessen any anticompetitive effects and promote competition in the industry.  On that front, a number of approaches have been proposed.   The FHFA and the Enterprises could encourage greater competition among data providers.  In addition to piloting supplemental credit scores that rely on alternative data sources outside those maintained by the CRAs, the Enterprises could test-and-learn or pilot other data sources and help provide some market discipline around the responsible use of various new and alternative data sources.  Fannie Mae has started using trended data provided by the CRAs, but a number of alternative data providers are developing sources that include rental payments, utility payments, telecommunications data, bank account transactions data (with consumer permission).  
The Enterprises should also revisit whether “the tri-merge credit report” or the practice of requiring mortgage lenders to obtain all three credit scores and reports, continues to be necessary.  Since the three CRAs provide virtually identical data and borrower coverage, the Enterprises could move away from requiring the tri-merge credit report.  As FHFA has noted in the non-mortgage lending market, (e.g., credit card, auto loans), it is common to use a single CRA source for credit scores and credit reports when underwriting credit risk. Because these lenders are able to choose which CRA to pull credit data from, these lenders receive competitive pricing on credit scores and credit reports from the CRAs.  The Enterprises could require two credit scores and reports instead of three, for example.
 Conclusion
We believe the Enterprises process to validate and approve credit score models has the potential to provide greater access to mortgage credit, and better mortgage products and loan pricing for a universe of consumers who have no credit history or thin credit files.  While other options can also work, we would support the comparison-based approach to evaluating the tests results from the various credit score models that FHFA has outlined in the proposal.  The comparison-based approach would allow an Enterprise flexibility to make any determination based on the results of the comparison.  However, the Enterprises should select those credit score models and data sources that are at least as accurate as current models if they would expand access to more borrowers.  The Enterprises should also take steps to mitigate the costs of any credit score adoption or transition on LMI borrowers.
Thank you for this opportunity to comment on this important matter.

Sincerely,	

National Community Reinvestment Coalition (NCRC)
Birmingham Business Resource Center
CASA of Oregon
Housing Education and Economic Development
Metropolitan Milwaukee Fair Housing Council
Pittsburgh Community Reinvestment Group
Woodstock Institute

© 2020 Federal Housing Finance Agency